| >> The agents are never told anything about the rules of the game, yet learn
about fundamental game concepts and effectively develop an intuition for CTF. Here we go again- throwing around big words, "intuition", and marring an
otherwise interesting piece of work. From a cursory glance at the relevant figure, "A look into how our agents
represent the game world" - it looks like what is being learned is very much a
goood old behaviour tree. For instance, the figure suggests that agents
learned to react to situations like "Agent flag at base & opponent flag at
base & not respawning & agent in home base". So basically, the condition part
of an IF-THEN-ELSE rule. Why is this called an "intuition" rather than a "rule"? From my reading, the
only reason is that it was learned by a deep neural net by reinforcement
learning without explicit supervision, i.e. without anyone telling the agent
"learn this rule". That's a very narrow, procrustean, definition of intuition. Is it really what
most people would mean by "intuition"? Is it even close? Who knows- nobody can
tell what most people would mean by "intuition". There's a dictionary
definition, but chances are most people would not know it by heart. So it's
very hard to even say "that's not what intuition means"- one would just be
begging the question. So why use such a vague term in an article like this, that is already pretty
impressive stuff? What do such meaningless claims add to the result? I don't
get it. |
If I play tennis for a while, I will get better at predicting where the ball will go after my opponent hits it merely because I have seen many combinations of shots and subsequent ball trajectories.
I think it would be weird to not call it an intuition just because it was learned by a deep neural net in this case.